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Two-dimensional information acquisition in social learning

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  • Bobkova, Nina
  • Mass, Helene

Abstract

We analyze a social learning model where the agents' utility depends on a common component and an idiosyncratic component. Each agent splits a learning budget between the two components. We show that information about the common component is fully aggregated if and only if agents do not have to sacrifice learning about their idiosyncratic component in order to learn marginally about the common component. If agents vary in how much they value their idiosyncratic component, then the order of agents can strictly impact how much information is aggregated.

Suggested Citation

  • Bobkova, Nina & Mass, Helene, 2022. "Two-dimensional information acquisition in social learning," Journal of Economic Theory, Elsevier, vol. 202(C).
  • Handle: RePEc:eee:jetheo:v:202:y:2022:i:c:s0022053122000412
    DOI: 10.1016/j.jet.2022.105451
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    References listed on IDEAS

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    1. Inga Deimen & Dezső Szalay, 2019. "Delegated Expertise, Authority, and Communication," American Economic Review, American Economic Association, vol. 109(4), pages 1349-1374, April.
    2. Lones Smith & Peter Sorensen, 2000. "Pathological Outcomes of Observational Learning," Econometrica, Econometric Society, vol. 68(2), pages 371-398, March.
    3. Kenneth Hendricks & Alan Sorensen & Thomas Wiseman, 2012. "Observational Learning and Demand for Search Goods," American Economic Journal: Microeconomics, American Economic Association, vol. 4(1), pages 1-31, February.
    4. Jacob Goeree & Thomas Palfrey & Brian Rogers, 2006. "Social learning with private and common values," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 28(2), pages 245-264, June.
    5. Manuel Mueller-Frank & Mallesh M. Pai, 2016. "Social Learning with Costly Search," American Economic Journal: Microeconomics, American Economic Association, vol. 8(1), pages 83-109, February.
    6. Ali, S. Nageeb, 2018. "Herding with costly information," Journal of Economic Theory, Elsevier, vol. 175(C), pages 713-729.
    7. Bikhchandani, Sushil & Hirshleifer, David & Welch, Ivo, 1992. "A Theory of Fads, Fashion, Custom, and Cultural Change in Informational Cascades," Journal of Political Economy, University of Chicago Press, vol. 100(5), pages 992-1026, October.
    8. Annie Liang & Xiaosheng Mu, 2020. "Complementary Information and Learning Traps," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 135(1), pages 389-448.
    9. Abhijit V. Banerjee, 1992. "A Simple Model of Herd Behavior," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 107(3), pages 797-817.
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    More about this item

    Keywords

    Information acquisition; Social learning; Information aggregation;
    All these keywords.

    JEL classification:

    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness

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